This page display the submited results for Action Leaderboards. For each submission, we display several main metrics in main table. For detailed information, more metrics, per-sequence results and visualisation (coming soon), please click submission name. For all tables, you can click headers to sort the results. Note you can download the submission zip file as well. Legends, metrics descriptions and reference are displayed after leaderboards table.

Individual Action Submissions

Name mAP

Mahsa Ehsanpour, Fatemeh Saleh, Silvio Savarese, Ian Reid, Hamid Rezatofighi JRDB-Act: A Large-scale Dataset for Spatio-temporal Action, Social Group and Activity Detection in arXiv

Mahsa Ehsanpour, Alireza Abedin, Fatemeh Saleh, Javen Shi, Ian Reid, Hamid Rezatofighi Joint Learning of Social Groups, Individuals Action and Sub-group Activities in Videos in ECCV2020

Additional Information Used

Symbol Description
Individual Image Method uses individual images from each camera
Stitched Image Method uses stitched images combined from the individual cameras
Pointcloud Method uses 3D pointcloud data
Online Tracking Method does frame-by-frame processing with no lookahead
Offline Tracking Method does not do in-order frame processing
Public Detections Method uses publicly available detections
Private Detections Method uses its own private detections

Evaluation Measures[1]

Measure Better Perfect Description
mAP/AP higher 100% For each detected bounding box in a key-frame, a model should predict a set of individual action labels. We report the the precision of the prediction


  1. The style and content of the Evaluation Measures section is reference from MOT Challenges.